Users of big data cognitive computing systems often desire to be notified of changes in analysis, decisions, and results as new data is received. Results pertaining to a particular query may be stored, and as more data is ingested into the system, the original query may be rerun with the new results compared to the old results. Users may then be alerted of any changes.
However, on a big data system, data updates are quite common and many may be insignificant to any particular user's goals. Users may then often be alerted to irrelevant and/or insignificant changes.
Thus, in a big data cognitive computing system, there is a need to determine which data changes are relevant to a particular user's query and significant enough to warrant notification to the user.